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Proceedings Paper

Using heuristic optimization to set SRAF rules
Author(s): ChangAn Wang; Norman Chen; Chidam Kallingal; William Wilkinson; Jian Liu; Alan Leslie
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Paper Abstract

A heuristic optimization approach has been developed to optimize SRAF (sub resolution assist feature) placement rules for advanced technology nodes by using a genetic algorithm. This approach has demonstrated the capability to optimize a rule-based SRAF (RBSRAF) solution for both 1D and 2D designs to improve PVBand and avoid SRAF printing. Compared with the MBSRAF based POR (process of record) solution, the optimized RBSRAF can produce a comparable PVBand distribution for a full chip test case containing both random SRAM and logic designs with a significant 65% SRAF generation time reduction and 55% total OPC time reduction.

Paper Details

Date Published: 24 March 2017
PDF: 10 pages
Proc. SPIE 10147, Optical Microlithography XXX, 1014706 (24 March 2017); doi: 10.1117/12.2258233
Show Author Affiliations
ChangAn Wang, GLOBALFOUNDRIES Inc. (United States)
Norman Chen, GLOBALFOUNDRIES Inc. (United States)
Chidam Kallingal, GLOBALFOUNDRIES Inc. (United States)
William Wilkinson, GLOBALFOUNDRIES Inc. (United States)
Jian Liu, GLOBALFOUNDRIES Inc. (United States)
Alan Leslie, GLOBALFOUNDRIES Inc. (United States)


Published in SPIE Proceedings Vol. 10147:
Optical Microlithography XXX
Andreas Erdmann; Jongwook Kye, Editor(s)

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